def main(): # EXAMPLE VideoId = 'tCXGJQYZ9JA' link = input("Enter Video : ") # link=H.my_form_post() i = 0 while (link[i] != '='): i = i + 1 id = link[i + 1:] # Fetch the number of comments # if count = -1, fetch all comments # count = int(input("Enter no. of comments to extract : ")) comments = CE.commentExtract(id, 100) possent = SYT.sentiment(comments) age = x.main() print('age is', age) print('positive content % is', possent) if (age > 0 and age < 5 and possent == 100): webbrowser.open(link) elif (age > 5 and age < 10 and possent > 90): webbrowser.open(link) elif (age > 10 and age < 15 and possent > 80): webbrowser.open(link) elif (age > 15 and age < 18 and possent > 75): webbrowser.open(link) elif (age > 18): webbrowser.open(link) else: print('not accessible')
def main(): # EXAMPLE VideoId = 'tCXGJQYZ9JA' videoId = input("Enter VideoId : ") # Fetch the number of comments # if count = -1, fetch all comments count = int(input("Enter no. of comments to extract : ")) comments = CE.commentExtract(videoId, count) SYT.sentiment(comments)
def main(): # Sample VideoId = '6lAUk0uQWEc' videoId = input("Enter VideoId : ") # Sample Tweets Keyword = 'Death Stranding' twitterQuery = input("Enter Twitter Hashtag/Keyword: ") # Fetch the number of comments # if count = -1, fetch all comments count = int(input("Enter no. of comments/tweets to extract : ")) comments = CE.commentExtract(videoId, count) SYT.sentiment(comments, twitterQuery, count)
def main(): userpositive = open("userpositive.txt", "w") userpositive.write("") userpositive.close() usernegative = open("usernegative.txt", "w") usernegative.write("") usernegative.close() # EXAMPLE VideoId = 'tCXGJQYZ9JA' videoId = input("Enter VideoId : ") # Fetch the number of comments # if count = -1, fetch all comments count = int(input("Enter no. of comments to extract : ")) comments = CE.commentExtract(videoId, count) SYT.sentiment(comments)
def main(): videoId = sys.argv[1] count = 20 comments = CE.commentExtract(videoId, count) SYT.sentiment(comments)
tags.append("No Tags") youtube_dict = {'pubDate': pubDate,'tags': tags,'channelId': channelId,'channelTitle': channelTitle,'categoryId':categoryId,'title':title,'videoId':videoId,'viewCount':viewCount,'likeCount':likeCount,'dislikeCount':dislikeCount,'favoriteCount':favoriteCount, 'commentCount':commentCount, 'keyword':keyword, 'url':url} df = pd.DataFrame(youtube_dict) df.sort_values(by='viewCount',ascending=False) import sentimentYouTube as SYT import comment_extract as CE import pandas as pd df['positive']='' df['negative']='' for i in df['videoId']: print(i) comments = CE.commentExtract(i,100) pos, neg = SYT.sentiment(comments) df.loc[df['videoId']==i,['positive']] = pos df.loc[df['videoId']==i,['negative']] = neg df = df[(df['positive']!='') | (df['negative']!='')] df.loc[:,'positive'] =df['positive'].astype(int) df.loc[:,'negative'] =df['negative'].astype(int) df.drop_duplicates(['videoId']) df['pubDate'] = pd.to_datetime(df.pubDate) df['publishedDate'] = df['pubDate'].dt.strftime('%d/%m/%Y') df1 = df[['keyword','publishedDate','title','viewCount','channelTitle','commentCount','likeCount','dislikeCount','tags','favoriteCount','videoId','channelId','categoryId','url','positive','negative']] df1.columns = ['keyword','publishedDate','Title','viewCount','channelTitle','commentCount','likeCount','dislikeCount','tags','favoriteCount','videoId','channelId','categoryId','URL','positive','negative'] export_csv = df1.to_csv (r'/home/YoutubeAPI/Result/youtube_search_keyword_{}.csv'.format(str(HariIni)), index = None, header=True)